基于数据和整体的航空网络静态定价模型

建立了一个静态定价与座位分配联合模型.利用模型的性质,将问题简化为一个可分的凹规划模型.特别地,在一个三航段网络上,从模型的网络流形式推出最优目标函数具有良好的性质,并对模型的最优价格决策进行了灵敏度分析.最后给出了一个双枢纽网络上对细分产品定价的算例.     

一类基于J=2且N=3的负载平衡网络的稳定性研究

考虑一个具有两个工作站而且每个工作站具有三个服务台的负载平衡网络.在该网络中,当某顾客进入网络或转移到下一个服务台中接受服务时,该顾客使用加入最短队列的策略.该网络的突出特点就是出现了检验数分布的概念以及属于同一工作站的服务台对称.本文先通过图形结合和不等式的一些简单性质证得三个条件相互等价,由于前人已经证明其中一个条件是网络稳定的必要条件,然后通过流体模型证得另外两个条件中的一个条件是网络稳定的充分条件,因此得到三个使得网络稳定的充分必要条件,更重要的是本文的结论证实了一个猜想.     

基于Granger因果检测的蛋白质信号网络建模

生物网络是一个非常复杂且具有随机性质的反馈网络,在不同的分子水平调控生物的功能.由于涉及大量分子间的相互作用,使得生物网络的建模面临极大的挑战.在本文中,对通常的Granger因果关系进行推广,将其应用到蛋白质网络的建模上,构建了一个11个蛋白质(PKC.PKA,Raf,Pkr,Jnk,P38,Mek,PIP3,PIP2,Akt,Erk)的相互作用网络.计算结果表明,本文提出的方法克服了Bayesian网络方法中存在的一些问题.如Bayesian网络计算量大,不能构建有环图.     

弹性光网络一类调度问题的一个新模型和算法

采用网络功能虚拟化技术的弹性光网络是一种新型的网络,其数据中心的合理部署,路由的科学规划及频谱的最优分配是一个关键而具有挑战的问题.为了解决这个问题,建立了弹性光网络资源分配和任务调度问题一个新的优化模型,新模型以虚拟网络功能在数据中心部署的负载最均衡,经过数据中心节点的路径最短以及频谱占用最少为目标,可同时使虚拟网络功能在数据中心部署,路径规划和频谱分配方案最优.为有效求解该模型,分别设计了一个经过所选数据中心的最短路径策略,虚拟网络功能在数据中心的部署策略以及频谱分配策略,构造了初始种群的产生方法,设计了新的变异算子,在此基础上,提出了求解模型的一个新的进化算法.最后进行了仿真实验,结果表明,最大频隙号和数据中心VNF部署数目的标准差相比对比算法有明显降低,验证了所建模型和算法的有效性.     

链式网络DEA模型

数据包络分析(DEA)是评价决策单元(DMU)相对有效性的一种工具,现已得到广泛的应用.传统的DEA不考虑系统内部结构,而是将系统作为一个"黑箱"来度量效率.针对多阶段网络结构提出一个新的网络DEA模型—链式网络DEA模型.研究网络决策单元的网络DEA有效性及各个阶段的弱DEA有效性之间的关系,给出了网络DEA有效的充分必要条件.若网络决策单元不是网络DEA有效的,根据模型可以指出系统在哪些阶段是无效的.     

排队网络在受限的优先服务原则下的稳定性

定义了一类新的服务原则—受限的优先服务原则.在这种服务原则下,一个标准处理网络被转化为一个特殊的批处理网络,为这类网络稳定性的判别提供了一种有效的思想方法.     

复杂网络中权重对舆情传播的影响

考虑到个体相互作用的差异以及个体状态的改变与其理性阈值相关,在均匀和非均匀网络上引入了权重概念,构建了舆情传播的阈值模型,利用蒙特卡罗方法模拟了传播动力学,研究了权重对网络鲁棒性的影响.当网络连通度较低时,存在一个最差权重指数,使得网络的鲁棒性最差;当网络连通度较高时,存在一个最优权重指数,使得网络的鲁棒性最好.     

基于非负矩阵理论的同步网络AIMD算法分析

利用非负矩阵理论提出了一个多源竞争共享带宽的网络模型.研究发现,满足模型假设的网络通常都有一个唯一的、全局指数收敛的稳态点.利用这个模型,分析了全局网络收敛到稳态点的收敛速度和稳定性.     

改进的最小费用理论在盲竖井选址中的应用

在网络的任意点求解绝对中心等特殊点是网络流研究的一个难点.在目前最小费用理论的基础上引入平面几何理论,把网络等效于几何图形,建立了数学模型.通过求解,得出了网络间的最佳连接点,从而确定出盲竖井的位置.最后以云南锡业集团个旧东区两个生产平台之间的连接为一算例,得出了理想的结果,验证了该方法的有效可行性.     

具有随机时延和丢包的网络控制系统的镇定新标准

研究了具有网络诱导时延和丢包的网络控制系统的镇定问题.在把随机时延和丢包看做对导数没有任何限制且满足Bernoulli分布的随机等价时延的基础上,根据等价时延在不同区间上的概率取值,给出了一个建立网络控制系统的新方法.基于Lyapunov稳定性理论,结合线性矩阵不等式方法,得到一个新的镇定标准.     

Modeling of spraying with time-dependent material feed rate

This paper presents a mathematical model for predicting the thickness of coatings deposited by means of spraying onto rotating parts with circular symmetry, for the case of time-dependent material feed rate. A procedure for calculating the material feed rate control law providing production of coatings with uniform thickness or coatings with a predefined law of thickness variation is developed. The proposed procedure was used to analyze the process of spraying onto the surface of a rotating disc. A material feed rate variation law providing production of uniform coatings and coatings with linear thickness variation is calculated. It is demonstrated that for the first case the optimal law of material feed rate variation is described by a linear function and for the second case it can be successfully approximated by a quadratic function. The proposed calculation technique can be easily used for the case of coatings with a more complex law of thickness variation.     

Probabilistic Analysis of Failures in Power Transmission Networks and Phase Transitions: Study Case of a High-Voltage Power Transmission Network

We present the failure analysis of a study case of a high-voltage power transmission network using the mathematical model of cascading blackouts introduced in Carreras et al. (Chaos 12:985–994, 2002). When the load of the network is randomly perturbed, we study the probability density function of the measure of the size of the resulting blackout as a function of the mean load level. The mathematical model used approximates the network with an undirected graph made of generator, load and junction nodes connected by branches representing the lines of the network. The electric flow in the network is found solving the optimal DC power-flow problem and the sequence of events causing a cascading blackout is simulated using a numerical scheme. The analysis points out the existence of values of the mean total power demand such that for higher values when the blackout size measure increases the decay of the blackout size measure probability density function changes from being best fitted by a negative exponential to being best fitted by an inverse power law. The analogies between this phenomenon and the phase transition phenomenon studied in statistical mechanics are discussed. The website: contains some auxiliary material including animations that helps the understanding of this paper. The numerical experience reported in this paper has been obtained using the computing grid of ENEA (Roma, Italy).     

Statistical Properties of a Generalized Threshold Network Model

The threshold network model is a type of finite random graph. In this paper, we introduce a generalized threshold network model. A pair of vertices with random weights is connected by an edge when real-valued functions of the pair of weights belong to given Borel sets. We extend several known limit theorems for the number of prescribed subgraphs and prove a uniform strong law of large numbers. We also prove two limit theorems for the local and global clustering coefficients.     

An Evolving Random Network and Its Asymptotic Structure

In this paper, we propose an evolving random network. The model is a linear combination of preferential attachment model and uniform model. We show that scaling limit distribution of the number of leaves at time $n$ is approximated by normal distribution and the proportional degree sequence obeys power law. The branching structure and maximum degree are also discussed in this paper.     

Morphisms and currents in infinite nonlinear resistive networks

In this paper we develop a theory of nonlinear resistive infinite electrical networks in the framework of modular sequence spaces. After introducing the notion of network morphism, we show that currents in infinite networks can be approximated by currents in suitable finite networks. Rayleigh monotonicity law for nonlinear networks is studied in detail. Parabolic and hyperbolic networks are introduced and characterized in analogy to the linear case.     

Large deviations and mean-field theory for asymmetric random recurrent neural networks

 In this article, we study the asymptotic dynamics of a noisy discrete time neural network, with random asymmetric couplings and thresholds. More precisely, we focus our interest on the limit behaviour of the network when its size grows to infinity with bounded time. In the case of gaussian connection weights, we use the same techniques as Ben Arous and Guionnet (see [3]) to prove that the image law of the distribution of the neurons' activation states by the empirical measure satisfies a temperature free large deviation principle. Moreover, we prove that if the connection weights satisfy a general condition of domination by gaussian tails, then the distribution of the activation potential of each neuron converges weakly towards an explicit gaussian law, the characteristics of which are contained in the mean-field equations stated by Cessac-Doyon-Quoy-Samuelides (see [4–6]). Furthermore, under this hypothesis, we obtain a law of large numbers and a propagation of chaos result. Finally, we show that many classical distributions on the couplings fulfill our general condition. Thus, this paper provides rigorous mean-field results for a large class of neural networks which is currently investigated in neural network literature. Received: 10 January 2000 / Revised version: 15 June 2001 / Published online: 13 May 2002     

Impulsive controller for wireless networked control system: Switched system approach

The problem of stabilization for wireless networked control system (NCS) with packet dropout and time delay is studied in this article. The impulsive control law for the NCS is defined with time delay and impulse. Using a switching model, the network‐induced imperfections can be treated as three switching subsystems. Therein, in the case of packet dropout, the control law use the previous state via the first‐order hold. The impulsive control law is designed using the switched system approach and the average dwell time method. The obtained sufficient conditions which can guarantee the exponential stability of switched system are in the form of linear matrix inequalities. Finally, a numerical example is used to demonstrate the merits and applicabilities of the proposed method. © 2015 Wiley Periodicals, Inc. Complexity 21: 291–299, 2016     

随机交通网络渐近连通可靠性分析

应用原有拓扑法获得城市交通网络的拓扑结构图,利用对偶拓扑法得到交通网络的对偶图,建立交通网络的随机网络模型。定义交通网络的渐近连通可靠性,得到路段连通可靠性、路网规模及整个路网连通可靠性之间的定量关系,结合随机图论、大数定律、渐近方法等证明所得结论;通过实例说明结论的应用价值。     

The challenges of statistical patterns of language: The case of Menzerath's law in genomes

The importance of statistical patterns of language has been debated over decades. Although Zipf's law is perhaps the most popular case, recently, Menzerath's law has begun to be involved. Menzerath's law manifests in language, music and genomes as a tendency of the mean size of the parts to decrease as the number of parts increases in many situations. This statistical regularity emerges also in the context of genomes, for instance, as a tendency of species with more chromosomes to have a smaller mean chromosome size. It has been argued that the instantiation of this law in genomes is not indicative of any parallel between language and genomes because (a) the law is inevitable and (b) noncoding DNA dominates genomes. Here mathematical, statistical, and conceptual challenges of these criticisms are discussed. Two major conclusions are drawn: the law is not inevitable and languages also have a correlate of noncoding DNA. However, the wide range of manifestations of the law in and outside genomes suggests that the striking similarities between noncoding DNA and certain linguistics units could be anecdotal for understanding the recurrence of that statistical law. © 2012 Wiley Periodicals, Inc. Complexity, 2012